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Guide users or agents to the correct MATLAB tool for processing large tabular data in file-based formats (CSV, Parquet, delimited text, spreadsheets, MDF) that may not fit in memory. Use when a user or agent mentions large files, big data, out-of-memory errors, OOM, scaling up, tall arrays, datastores, or needs to process multiple tabular files. Covers the decision between datastore + tall, datastore + transform, and parallel execution. Also use when a user or agent has working in-memory code (readtable, parquetread) that runs out of memory and needs a migration path. Also covers building custom datastore classes for proprietary or non-standard formats — use when the task requires subclassing matlab.io.Datastore, implementing a custom reader, building an extensible datastore, or integrating a new file format with tall arrays or parallel computing. Do NOT use for MAT files (use matfile instead).

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当实现用户驱动的大文件导出或批量序列化（Excel/CSV/JSON/JSONL/PDF，数据量未知或超过 1 万行/10 MB）时触发；普通小文件下载、静态资源下载、非导出 Writer/Report 类不触发。防止 OOM、临时文件残留、同步导出阻塞 HTTP 线程和表格公式注入。

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当代码涉及 Excel/CSV/JSON/PDF 大文件导出、批量序列化、内存里构建大对象时触发。防止 OOM、临时文件残留、同步导出阻塞 HTTP 线程等内存安全陷阱。

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Use when setting up URP (or choosing URP vs HDRP), configuring URP assets and quality tiers for PC and phones, lighting a stylized or realistic Unity scene (sun, sky, baked or mixed lightmaps, Shadowmask, Adaptive Probe Volumes, reflection probes), or fixing blurry shadows, light leaks, gray bakes, washed-out images, tonemapping and grading, bloom too expensive on mobile, TAA, STP or MSAA choices, GPU Resident Drawer setup, shader warm-up hitches, or a custom shader that vanished or lost its baked light.

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Use when building a 2D game in Unity 6.3 URP: pixel-art or HD sprite import and PPU, sprite atlases, Tilemaps, Rule Tiles and reskins, the 2D Renderer and 2D lights with normal maps, 2D animation, a platformer or top-down controller ("make a platformer controller that feels good", coyote time, jump buffer, one-way platforms, spikes), Pixel Perfect Camera, a follow or room camera, hit stop and screen shake; or when pixel art looks blurry or shimmers, tiles show seams, 2D lights do nothing or cost too much, the jump feels floaty, or the camera loses the player when falling.

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Use when lighting, rendering or compositing in Blender: light a character, product or hero shot, interior at dusk or night, three-point or motivated lighting, sun and sky, HDRI, EEVEE vs Cycles settings, light leaks or noise, flat or muddy renders, subject not standing out, AgX/ACES color management, render passes, EXR, light groups, bloom and vignette in the 5.x compositor, rule of thirds and value checks, toon/NPR looks, or judging a render like a lighter.

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Guidance on implementing the Data Layer using Repository pattern, Room (Local), and Retrofit (Remote) with offline-first synchronization.

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Builds real-time communication systems with WebSockets or Socket.IO including bidirectional messaging, horizontal scaling with Redis, presence tracking, and room management.

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Cross-functional what-if modeling for compound adversity -- shows how one problem cascades into the next. Use when facing complex risk scenarios, strategic decisions with major downside, or multi-variable threats.

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Cascades strategy from boardroom to individual contributor and detects misalignment. Use when teams pull in different directions, OKRs don't connect, departments optimize locally at company expense, or strategy doesn't translate to execution.

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Comprehensive Scrum Master assistant for sprint planning, backlog grooming, retrospectives, capacity planning, and daily standups with intelligent context-aware reporting

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Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.

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Acknowledge a tap/click with a ripple that blooms from the exact press point. Fast and low-opacity so it reads as feedback, not decoration. No ripple under prefers-reduced-motion (native :active covers it). Avoid on destructive actions and text links.

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When you want to model personal financial scenarios — house purchase + rental income (ADU, bedroom rentals, house-hacking), renovation budgets, monthly cash flow, big-purchase decisions, savings/investment what-ifs for a household. Ships with a house scenario template; other scenarios (refi, car, education, retirement, side income) slot in as templates. Outputs markdown scenario comparison tables. Saves scenarios to ~/Documents/personal-cfo/ with an index in ~/.config/makerskills/personal-cfo/archive/. Composes with decide, deep-research (rental comps, rates), business-brainstorm, second-brain. Triggers on "/personal-cfo," "model this scenario," "house math," "rental forecast," "monthly cash flow," "what if I rent out the ADU," "compare these housing scenarios," "should we buy this house," "house-hack math," "renovation budget."

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When you paste raw human input — a call transcript (Grain, Zoom, Granola, Fathom), a text or email from a client/partner/friend, a voice-memo dump, or meeting notes — and want it converted into structured work. Extracts decisions, action items (yours vs theirs), bugs/feature requests, and facts worth keeping; files GitHub issues in the right repo, captures to the second-brain vault, and drafts (never sends) the reply. Triggers on "/ingest", "ingest this", "here's my call with X," "here's the transcript," "this is from [person]," "[person] asked me this," "from [person]:", a pasted transcript with speaker labels, or a forwarded client message that clearly expects processing. Person→project routing lives in a private config; unknown senders get asked about once, then remembered.

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Design trauma-informed classroom practices that prioritise safety, predictability, connection, and regulation. Use when student behaviour may be trauma-related or the class needs a sensitive approach.

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Map a current event below the surface into patterns, structures, and mental models. Use when a class or team needs systemic understanding before action.

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Select and configure a structured discussion protocol matched to the purpose, topic, and group readiness. Use when planning classroom discussions, Socratic seminars, or structured debate.

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Design a focused lesson observation protocol with specific look-fors and evidence collection methods. Use when planning peer observations, coaching visits, or developmental classroom visits.

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Translate an external competency framework like DigComp, GreenComp, or ISTE into classroom-ready activities. Use when implementing framework standards in specific teaching contexts.

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Orchestrate compassionate systems tools from issue or aspiration to wise action. Use when a class needs a complete inquiry workflow.

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Adapt a historical primary source for classroom use — modifying complexity and length while preserving features for sourcing, close reading, and corroboration. Use when a primary source is too complex for the target age group.

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Adapt a classroom task for specific learner needs while preserving the core learning objective intact. Use when differentiating for SEND, EAL, gifted, ADHD, dyslexia, or anxiety.

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Map which elements of an assignment benefit from AI assistance vs. which AI use undermines. Use when redesigning tasks for AI-age classrooms or setting defensible AI use policies for specific assignments.

日本語の概要は準備中です。原文の説明を表示しています。